The growing number of e-commerce orders is leading to increased risk management to
prevent default in payment. Default in payment is the failure of a customer to settle a bill …

Geometric semantic genetic programming (GP) has recently attracted much attention. The
key innovations are inducing a unimodal fitness landscape in the semantic space and …

Symbolic regression (SR) is an important problem with many applications, such as
automatic programming tasks and data mining. Genetic programming (GP) is a commonly …

Genetic programming (GP) is one of the commonly used tools for symbolic regression. In the
field of GP, the use of semantics and an external library of subexpressions for designing …

Recent advances in geometric semantic genetic programming (GSGP) have shown that the
results obtained by these methods can outperform those obtained by classical genetic …

Semantic GP is a promising branch of GP that introduces semantic awareness during
genetic evolution to improve various aspects of GP. This paper presents a new Semantic GP …

Objectives Proinflammatory cytokines released during inflammation can cause
hyperexcitability in pain transmission neurons, leading to hyperalgesia and allodynia …

A recent discovery has attracted the attention of many researchers in the field of genetic
programming: given individuals with particular characteristics of alignment in the error …

Semantic GP is a promising approach that introduces semantic awareness during genetic
evolution. This paper presents a new Semantic GP approach based on Dynamic Target …

In 2013, our research group published a contribution in which a new version of genetic
programming, called Geometric Semantic Genetic Programming (GSGP), was fostered as an …